Users are increasingly able to interact with computers using natural language, e.g., in what will be referred to herein as “human-to-computer dialogs.” For example, many mobile computing devices such as smart phones, tablets, smart watches, standalone smart speakers, and so forth, include software programs referred to as “automated assistants” (a.k.a. “interactive assistant modules,” “mobile assistants,” etc.). Automated assistants may be configured to parse and interpret natural language input (e.g., spoken first then converted to text, or received initially as text) and provide responsive output, such as answers to questions, task initiation, etc. Existing automated assistants often have difficulty switching between domains of conversation. For example, if a user and an automated assistant have been exchanging dialog about a subject in one topic or domain (e.g., playing a game), and then the user abruptly steers the conversation towards another topic in an unrelated domain (e.g., weather), the automated assistant may not be entirely responsive and/or may require additional dialog to properly respond. One possible reason is that automated assistants tend to be created and/or maintained by a relatively small number of entities (e.g., a single developer). It may be difficult for such a small number of entities to anticipate how users may transition between innumerable possible conversational domains/topics and design robust dialogs, grammars, etc., for each such domain/topic.